tf.contrib.distributions.matrix_diag_transform(matrix, transform=None, name=None) Transform diagonal of [batch-]matrix, leave

tf.contrib.distributions.Gamma.event_shape(name='event_shape') Shape of a single sample from a single batch as a 1-D int32 Tensor

tf.contrib.distributions.Normal.prob(value, name='prob') Probability density/mass function (depending on is_continuous)

tf.contrib.distributions.MultivariateNormalDiag.parameters Dictionary of parameters used by this Distribution.

tf.contrib.distributions.StudentT.log_survival_function(value, name='log_survival_function') Log survival function.

tf.contrib.distributions.Exponential.batch_shape(name='batch_shape') Shape of a single sample from a single event index as a 1-D

tf.contrib.distributions.MultivariateNormalDiagWithSoftplusStDev.param_static_shapes(cls, sample_shape) param_shapes with static

tf.contrib.distributions.Uniform.std(name='std') Standard deviation.

tf.contrib.distributions.ExponentialWithSoftplusLam.sample(sample_shape=(), seed=None, name='sample') Generate samples of the

class tf.contrib.distributions.Uniform Uniform distribution with a and b parameters.